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» How to Dynamically Merge Markov Decision Processes
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QEST
2010
IEEE
14 years 7 months ago
Symblicit Calculation of Long-Run Averages for Concurrent Probabilistic Systems
Abstract--Model checkers for concurrent probabilistic systems have become very popular within the last decade. The study of long-run average behavior has however received only scan...
Ralf Wimmer, Bettina Braitling, Bernd Becker, Erns...

Publication
151views
13 years 8 months ago
Robust Bayesian reinforcement learning through tight lower bounds
In the Bayesian approach to sequential decision making, exact calculation of the (subjective) utility is intractable. This extends to most special cases of interest, such as reinfo...
Christos Dimitrakakis
AAAI
2004
14 years 11 months ago
Dynamic Programming for Partially Observable Stochastic Games
We develop an exact dynamic programming algorithm for partially observable stochastic games (POSGs). The algorithm is a synthesis of dynamic programming for partially observable M...
Eric A. Hansen, Daniel S. Bernstein, Shlomo Zilber...
AAAI
2011
13 years 9 months ago
Linear Dynamic Programs for Resource Management
Sustainable resource management in many domains presents large continuous stochastic optimization problems, which can often be modeled as Markov decision processes (MDPs). To solv...
Marek Petrik, Shlomo Zilberstein
NIPS
2001
14 years 11 months ago
Predictive Representations of State
We show that states of a dynamical system can be usefully represented by multi-step, action-conditional predictions of future observations. State representations that are grounded...
Michael L. Littman, Richard S. Sutton, Satinder P....